Arterial Performance Measures using MAC Readers – Portland’s Experience

NATMEC ConferenceJune 23rd, 2010

Shaun Quayle, P.E.; Kittelson & Associates, Inc.Peter Koonce, P.E.; City of Portland

Presentation OverviewPresentation Overview

The Journey How did we get here?

Does this really work? Validation

MAC Reader Applications Travel time & OD

What’s next?

Presentation InspirationPresentation Inspiration

What gets measured gets done– We collect data on our arterial street system

– We need to convert that data into information better decisions

Example: Gauge travel time competitiveness of transit vs. auto modes?

– Transit performance with our Automatic Vehicle Location System

– Probe vehicle travel times via MAC readers

– Transit signal priority or transit operations changes?

Presentation InspirationPresentation Inspiration

What data do we want?– NCHRP 3-79 describes significant amount of techniques including

wireless

– Aha! Moment in the research

What data can we get inexpensively now?– MAC Address readers probe data

MAC Reader Technology OverviewMAC Reader Technology Overview

Media Access Control (MAC) = unique identifier by manufacturer, 48 bit (>28 trillion) charactersBluetoothTM = common name for wireless radio frequency communication protocol between electronic devices

00:1E:3D:AF:DA:C5

Auto

Pedestrian

Bike

Bus/LRT

TEXT FILE

MS ACCESS FILE

PERSONAL DEVICE

FIELD RADIO &

ANTENNA

MINI COMPUTER (IN CABINET)

OUTPUT

KAI CUSTOM SOFTWARE

Truncated MAC Address

MAC Address Matching – Probe SampleMAC Address Matching – Probe Sample

STATION 1 STATION 2

Address First Detected On Last Detected On

00:10:86:e8:56:14 9:05:44 PM 9:05:44 PM00:1e:45:69:4d:1f 9:12:00 PM 9:12:00 PM00:15:b9:d2:82:e2 9:18:40 PM 9:18:40 PM

Address First Detected On Last Detected On

00:10:86:e8:56:14 9:05:44 PM 9:05:44 PM00:1e:45:69:4d:1f 9:12:00 PM 9:12:00 PM00:15:b9:d2:82:e2 9:18:40 PM 9:18:40 PM

Address First Detected On Last Detected On

00:1c:c1:7b:b7:06 9:06:09 PM 9:06:09 PM00:c0:1b:04:d6:9d 9:06:09 PM 9:07:10 PM00:1e:45:69:4d:1f 9:06:48 PM 9:06:48 PM00:1c:cc:90:12:d7 9:10:24 PM 9:10:24 PM00:15:b9:d2:82:e2 9:12:45 PM 9:12:45 PM

Address First Detected On Last Detected On

00:1c:c1:7b:b7:06 9:06:09 PM 9:06:09 PM00:c0:1b:04:d6:9d 9:06:09 PM 9:07:10 PM00:1e:45:69:4d:1f 9:06:48 PM 9:06:48 PM00:1c:cc:90:12:d7 9:10:24 PM 9:10:24 PM00:15:b9:d2:82:e2 9:12:45 PM 9:12:45 PM

First to First

First to First Last to Last

Last to Last

The Journey – EquipmentThe Journey – Equipment

The Journey – Software AutomationThe Journey – Software Automation

Converts raw data to database

Filtering by reference– First-First, Last-Last, etc.

Clock correction, if needed

Capture statistics – data integrity check– Raw individual records

– Grouped by hour by station- # Pings- # of Hits/Devices

The Journey – Software AutomationThe Journey – Software Automation

Output = graphical and tabular

Does it work? Tualatin-Sherwood Pilot StudyDoes it work? Tualatin-Sherwood Pilot Study

Tualatin-Sherwood Road (SW Portland Suburbs)~2.5 miles in length~40,000 ADT – 4 lane commercial arterial

MAC reader locations

AVERY STREET

FRED MEYER ACCESS

NYBERG / 65th

MANUAL FLOATING CAR TRAVEL TIME RUNS

MAC Reader Corridor Test 1MAC Reader Corridor Test 1

Objectives– Compare manual vs. MAC travel times

Manual floating car GPS travel time runs– Approximately 12 two-way trips (3 drivers)

– Low sample, one day and only in peak hours

MAC Reader Technology Deployment– 24 hours/7 days a week

– 9 days

– Capture rate ~ 3 to 4% of ADT

Travel Time Profile (~9 days)Travel Time Profile (~9 days)Travel Time Profile (~9 days)

Between Fred Meyer and Avery - 24 Hour

-1000

-800

-600

-400

-200

0

200

400

600

800

1000

4:00 6:00 8:00 10:00 12:00 14:00 16:00 18:00 20:00 22:00

Trav

el T

ime

(Sec

onds

)

MAC Reader Manual

Westbound

Eastbound

Travel Time: Manual vs. MAC ValidationTravel Time: Manual vs. MAC Validation

Manual trend shows increasing travel time, while MAC shows end

of congestion

MAC points match manual points

0

200

400

600

800

1000

1200

1400

1600

1800

2000

2/12/09 12:00 AM

2/12/09 12:00 PM

2/13/09 12:00 AM

2/13/09 12:00 PM

2/14/09 12:00 AM

PM Peak Travel Time is approximately 3x mid day travel time

Travel Time Profile – Trend ExplorationTravel Time Profile – Trend Exploration

?

MAC Reader Application – Identify and Address InefficienciesMAC Reader Application – Identify and Address Inefficiencies

Travel Time – Running Speeds– Corridor character pass-by or

mode split?

– Affect of operational changes signal timing and incident example

Origin-Destination– Linear for signal progression

– Network for routing – travel demand model / trip distribution

Corridor Travel Character thru MAC ReadersCorridor Travel Character thru MAC Readers

Observed Travel Times WB Johnson Creek Blvd from 92nd Avenue (2012) to 82nd Avenue (2011)

0

200

400

600

800

1000

1200

02/18/1012:00:00

02/20/1012:00:00

02/22/1012:00:00

02/24/1012:00:00

02/26/1012:00:00

02/28/1012:00:00

Trav

el T

ime

(s)

Observed Travel Times NB 82nd Avenue from Sunnyside (2013) to JCB (2011)

0

200

400

600

800

1000

1200

1400

02/19/1000:00:00

02/20/1000:00:00

02/21/1000:00:00

02/22/1000:00:00

02/23/1000:00:00

02/24/1000:00:00

02/25/1000:00:00

02/26/1000:00:00

02/27/1000:00:00

02/28/1000:00:00

Trav

el T

ime

(s)

Travel Time Record Suspected Pass-by Trip

Many Pass-By or Non-Auto Mode Trips

Heavy Retail Corridor

Few Pass-By or Non-Auto Trips

Heavy Office-Residential Corridor

Observed Travel Times from Powell & 33rd to Powell & 21st

0.0

50.0

100.0

150.0

200.0

250.0

300.0

350.0

400.0

450.0

05/11/1000:00:00

05/11/1012:00:00

05/12/1000:00:00

05/12/1012:00:00

05/13/1000:00:00

05/13/1012:00:00

05/14/1000:00:00

05/14/1012:00:00

05/15/1000:00:00

Trav

el T

ime

(s)

Average Travel Time Travel Time Record Discarded Travel Time Record

Recurring Weekday AM Peak IncidentRecurring Weekday AM Peak Incident

Morning Arterial Congestion

MAC Reader Detected Recurring Weekday AM Peak IncidentMAC Reader Detected Recurring Weekday AM Peak Incident

Observed Travel Times WB Harmony Road from 82nd Avenue (2013) to Linwood Avenue (2019)

0

100

200

300

400

500

600

02/22/1012:00:00

02/23/1012:00:00

02/24/1012:00:00

02/25/1012:00:00

02/26/1012:00:00

02/27/1012:00:00

Trav

el T

ime

(s)

Travel Time Record Hourly Average Travel Time

Morning Congestion or Heavy Rail Train?

-2000

-1600

-1200

-800

-400

0

400

800

1200

1600

2000

Sunday Monday Tuesday Wednesday Thursday Friday Saturday Sunday

February March

Before (Orange) and After (Blue) Signal Timing ChangeBefore (Orange) and After (Blue) Signal Timing Change

Significant reduction in travel time and variability

Westbound

Eastbound

0

400

800

1200

1600

2000

4:00 6:00 8:00 10:00 12:00 14:00 16:00 18:00 20:00

February March

Before (Orange) and After (Blue) Timing ChangeBefore (Orange) and After (Blue) Timing Change

Westbound

Impact of Signal Timing ChangeImpact of Signal Timing Change

0.20.7-4-23Difference

18.819.4366336March

19.020.1371360February

PM

2.94.3-40-57Difference

23.925.1291278March

21.020.8332335February

AM

WestEastWestEast

Speed (mph)Travel Time (sec.)

MAC Probe Data – Origin-Destination SamplingMAC Probe Data – Origin-Destination Sampling

Regional travel demand model comparisons

Route selection

Progression analyses

MAC Probe Data – OD Sampling for Route Selection MAC Probe Data – OD Sampling for Route Selection

MAC Probe Data – OD Sampling vs. Regional TDM MAC Probe Data – OD Sampling vs. Regional TDM

What’s Next?What’s Next?

City of Portland/ODOT Permanent MAC Reader Pilot – Powell Boulevard

– Real-time and archived travel speed/time data publish for traveler information

– Testing permanent equipment

– Testing communication system and determining best permanent practices

What’s Next?What’s Next?

City of Portland/ODOT Permanent MAC Reader Pilot – Powell Boulevard

– In-Step with SCATS Adaptive Project

–

-1200

-1100-1000

-900

-800

-700

-600

-500

-400

-300

-200

-100

0

100200

300

400

500600

700

800

900

1000

1100

1200

Sunday Monday Tuesday Wednesday Thursday Friday Saturday Sunday

February March

Westbound

Eastbound

Summary MAC Probe BenefitsSummary MAC Probe Benefits

Higher amounts of collected data– Highway & arterial travel times, running speeds, and origin-

destination

– Off-peak & weekend; 7 days a week

Permanent or temporary deployment– Future communications infrastructure integration

Cost Effectiveness– Easily attainable data for relatively low costs compared to

existing technologies and techniques- Compare to GPS travel time runs- Compare to license plate surveys

Summary MAC Probe ChallengesSummary MAC Probe Challenges

Travel Time Outliers (pass-by trips, peds, etc.)– Good data vs. bad data

– “Average” travel times

– Multiple modes

Fidelity – Data is macroscopic

– No “stop” data

Strategic placement– Influences of variable traffic conditions

– Mid-block is preferred, but not always available

ReferencesReferences

NCHRP 3-79: Predicting Travel Speeds for Urban Streets

MAC Address Tracking– Wasson, J.S., J.R. Sturdevant, D.M. Bullock, “Real-Time Travel Time Estimates Using MAC

Address Matching,” Institute of Transportation Engineers Journal, ITE, Vol. 78, No. 6, pp. 20-23, June 2008.

– Bullock, D.M., C.M. Day; J.S. Sturdevant, ”Signalized Intersection Wasson J.S., S.E. Young, J.R. Sturdevant, P.J. Tarnoff, J.M. Ernst, and D.M. Bullock, , “Evaluation of Special Event Traffic Management: The Brickyard 400 Case Study”.

– Malinovskiy, Y., Y.J. Wu, Y. Wang, U. Lee, “Field Experiments on Bluetooth-based Travel Time Data Collection.” TRB 89th Annual Meeting, Washington D.C., 2010.

Questions?Questions?

Shaun Quayle, Kittelson & Associates, Inc.– squayle@kittelson.com

Peter Koonce, City of Portland– Peter.Koonce@portlandoregon.gov